Defining and identifying cell sub-crosstalk pairs for characterizing cell–cell communication patterns

Current cell–cell communication analysis focuses on quantifying intercellular interactions at cell type level. In the tissue microenvironment, one type of cells could be divided into multiple cell subgroups that function differently and communicate with other cell types or subgroups via different ligand–receptor-mediated signaling pathways. Given two cell types, we define a cell sub-crosstalk pair (CSCP) as a combination of two cell subgroups with strong and similar intercellular crosstalk signals and identify CSCPs based on coupled non-negative matrix factorization. Using single-cell spatial transcriptomics data of mouse olfactory bulb and visual cortex, we find that cells of different types within CSCPs are significantly spatially closer with each other than those in the whole single-cell spatial map. To demonstrate the utility of CSCPs, we apply 13 cell–cell communication analysis methods to sampled single-cell transcriptomics datasets at CSCP level and reveal ligand–receptor interactions masked at cell type level. Furthermore, by analyzing single-cell transcriptomics data from 29 breast cancer patients with different immunotherapy responses, we find that CSCPs are useful predictive features to discriminate patients responding to anti-PD-1 therapy from non-responders. Taken together, partitioning a cell type pair into CSCPs enables fine-grained characterization of cell–cell communication in tissue and tumor microenvironments.

The top left section of heatmap shows the expression of PD-1 in CD8+ T cells from patients who respond to anti-PD-1 therapy.The bottom left section shows the expression of PD-1 in CD8+ T cells from patients who do not respond to therapy.The top right section shows the average expression of PD-L1 and PD-1 in macrophages and CD8+ T cells from patients who respond to therapy.The bottom right section shows the average expression of PD-L1 and PD-1 in macrophages and CD8+ T cells from patients who do not respond to therapy.

Fig S12. Comparison of gene expression based on different dimensionality reduction method.
The box plot shows the z-scores of PD-1 expression in CSCPs (top section), z-scores of PD-1 expression in cell subtypes (middle section), and z-scores of the expression of PD-L1 and PD-1 in CSCPs (bottom section) after different dimension reduction techniques, including linear discriminant analysis (LDA), principal component analysis (PCA), and multidimensional scaling (MDS).The dark orange color represents response to anti-PD-1 therapy, while the light orange color represents no response to anti-PD-1 therapy.

Fig S2 .
Fig S2.The stability comparison of coupled NMF with and without L2 regularization.The box plot shows the similarity between the results of multiple executions of coupled NMF (10 times for each dataset) is quantified using (A) Adjusted Rand Index (ARI) and (B) Normalized Mutual Information (NMI).The green box represents the similarity based on coupled NMF with L2 regularization, while the grey box represents similarity without L2 regularization.

Fig S4 .
Fig S4.Visualization of cell spatial location and average distance between microglia cells and endothelial cells in (A) olfactory bulb, FOV0, (B) olfactory bulb, FOV4, (C) visual cortex, FOV0 and (D) visual cortex, FOV5.The red squares represent the sender cells in CSCP-1, the blue squares represent the receiver cells in CSCP-1, the red triangles represent the sender cells in CSCP-2, the blue triangles represent the receiver cells in CSCP-2.The grey bar represents the average distance of cells within cell types.(OB, olfactory bulb; VC, visual cortex)

Fig
Fig S6.The Jaccard coefficient of 13 cell-cell communication methods and 12 cell type pairs in mouse M002.The top section displays the box plot of Jaccard coefficient for each cell-cell communication methods.The bottom section displays the bar plot of Jaccard coefficient for each cell-cell communication methods in each cell type pairs.

Fig
Fig S8.The Jaccard coefficient of 13 cell-cell communication methods and 12 cell type pairs in mouse F002.The top section displays the box plot of Jaccard coefficient for each cell-cell communication methods.The bottom section displays the bar plot of Jaccard coefficient for each cell-cell communication methods in each cell type pairs.

Fig S10 .
Fig S10.The diagram of dimension reduction and normalization of expression and average expression.The expression of cell subtype and CSCPs for each patient is condensed into a single dimension using linear dimensionality reduction (LDA).Subsequently, z-score normalization is applied to the one-dimensional expression of cell type, cell subtype, and CSCPs for all patients individually.

Fig S11 .
Fig S11.The dimensionality-reduced and normalized expression of each feature for each patient.The top left section of heatmap shows the expression of PD-1 in CD8+ T cells from patients who respond to anti-PD-1 therapy.The bottom left section shows the expression of PD-1 in CD8+ T cells from patients who do not respond to therapy.The top right section shows the average expression of PD-L1 and PD-1 in macrophages and CD8+ T cells from patients who respond to therapy.The bottom right section shows the average expression of PD-L1 and PD-1 in macrophages and CD8+ T cells from patients who do not respond to therapy.